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--- |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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- wer |
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- chrf |
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model-index: |
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- name: Whisper Base GA-EN Speech Translation |
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results: [] |
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datasets: |
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- ymoslem/IWSLT2023-GA-EN |
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language: |
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- ga |
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- en |
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library_name: transformers |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Base GA-EN Speech Translation |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset. |
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The best model based on ChrF (this version) is at checkpoint 1000, epoch 3.72, and it achieves the following results on the evaluation set: |
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- Loss: 2.2482 |
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- Bleu: 20.8 |
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- Chrf: 35.56 |
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- Wer: 84.0162 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 0.03 |
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- training_steps: 1000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:| |
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| 1.5709 | 0.37 | 100 | 2.1099 | 5.49 | 22.56 | 144.5745 | |
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| 0.9426 | 0.74 | 200 | 2.0613 | 10.65 | 26.37 | 130.0315 | |
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| 0.3912 | 1.12 | 300 | 2.1207 | 13.43 | 29.77 | 103.9172 | |
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| 0.3943 | 1.49 | 400 | 2.1177 | 16.64 | 32.27 | 97.3435 | |
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| 0.3605 | 1.86 | 500 | 2.1689 | 18.41 | 32.69 | 87.1679 | |
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| 0.1164 | 2.23 | 600 | 2.1506 | 20.49 | 33.74 | 82.3953 | |
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| 0.1371 | 2.6 | 700 | 2.1397 | 19.86 | 34.97 | 84.9167 | |
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| 0.1263 | 2.97 | 800 | 2.1849 | 21.11 | 34.92 | 81.3147 | |
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| 0.049 | 3.35 | 900 | 2.2424 | 21.24 | 35.22 | 83.6110 | |
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| 0.0462 | 3.72 | 1000 | 2.2482 | 20.8 | 35.56 | 84.0162 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
